Next generation of medical professionals underprepared for machine learning, say researchers
Medical school and residency programs have an untapped opportunity to educate clinicians about using AI in patient care.
Graduate medical education and other teaching programs within academic teaching hospitals across the U.S. have not yet come to grips with educating students and trainees on the emerging technology of artificial intelligence driven by machine learning, new research shows.
THE EXPECTED IMPACT
Using a PubMed search with "machine learning" as the medical subject heading term, the researchers found that the number of papers published on the topic has increased since the beginning of this decade. In contrast, the number of publications related to undergraduate and graduate medical education have remained relatively unchanged since 2010.
Realizing the need for educating the students and trainees within the Boston University Medical Campus about machine learning, corresponding author Vijaya Kolachalama designed and taught an introductory course at BUSM.
The course is intended to educate the next generation of medical professionals and young researchers with biomedical and life sciences backgrounds about machine learning concepts and help prepare them for the ongoing data science revolution.
The authors hope their perspective article stimulates medical school and residency programs to think about the progressing field of AI and how to use it in patient care. The authors believe that if medical education begins to implement machine learning curriculum, physicians may begin to recognize the conditions and future applications where AI could potentially benefit clinical decision making and management early on in their career, and be ready to utilize these tools better when beginning practice.
THE BIGGER TREND
Artificial intelligence driven by machine learning algorithms is a branch in the field of computer science that is rapidly gaining popularity within the healthcare sector. Last month, an Accenture report projected that insurers can save up to $7 billion over 18 months using technologies driven by AI. About three-quarters, or 72 percent of payer executives, said AI will be one of their top three strategic priorities for their organization within the year.
That's just one of many examples. Hospitals are also using AI and machine learning for back office operations, billing, as well as care delivery. And with physicians and now even surgeons, growing encumbered by EHRs, just about anything doctors can automate will be welcome in the future. AI, for instance, is also expected to among the ways innovators address physician burnout, though not the only one.
Twitter: @JELagasse
Email the writer: jeff.lagasse@himssmedia.com